Welcome to Yuwei Luo's Homepage

I am a fifth-year Ph.D. student in Operations, Information & Technology at Stanford Graduate School of Business. I am fortunate to be advised by Prof. Mohsen Bayati.

I received my M.S. degree in Statistics at University of Chicago. and B.S. degree in Mathematics and Applied Mathematics at School of the Gifted Young, University of Science and Technology of China (USTC).

Here is a copy of my CV.

Research Interest

My research interest broadly lies in reinforcement learning, optimization, bandits, experiment design, causal inference, and large language models.

Can We Validate Counterfactual Estimations in the Presence of General Network Interference? [preprint]

Geometry-Aware Approaches for Balancing Performance and Theoretical Guarantees in Linear Bandits [paper]

The International Conference on Learning Representations (ICLR), 2025

Higher-Order Causal Message Passing for Experimentation with Complex Interference [paper]

Conference on Neural Information Processing Systems (NeurIPS), 2024

Adaptive Design of Clinical Trials: A Sequential Learning Approach

Major Revision, Operations Research

Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems [paper]

SIGMETRICS 2022 / Proceedings of the ACM on Measurement and Analysis of Computer Systems 6(1)

Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees [paper]

International Conference on Machine Learning (ICML), 2020

Nesterov's Accelerated Gradient Method and Sprays on Manifolds [working paper]

Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator [preprint]

Ph.D. in Operations, Information & Technology, Stanford University Graduate School of Business, 09/2020 - Present
M.S. in Statistics, The University of Chicago, 09/2018 – 03/2020
B.S. in Mathematics and Applied Mathematics, University of Science and Technology of China, 09/2014 – 07/2018

Email: yuweiluo [at] stanford.edu